An Incentive Mechanism Model of Credit Behavior of SMEs Based on the Perspective of Credit Default Swaps
Bibliographic record
Abstract
The rapid development of credit default swap (CDS) market has changed the manner of credit risk management of banks to some extent and has had a new influence on the bank-enterprise credit model. In this study, the credit financing process of credit risk in small- and medium-sized enterprises (SMEs) gathers within a bank, which makes it difficult for SMEs to raise funds. On the basis of the perspective of CDS, we construct an incentive game model of bank-enterprise credit behavior and analyze the influence mechanism of the credit financing of SMEs on CDS contract coupon rate, CDS payout ratio, bank-enterprise credit effort, and loan recovery rate when considering CDS. The result shows that the CDS contract leads to insufficient supervision after a bank loan, the moral hazard of the SMEs rises, and the probability of credit default events increases. In addition, in view of CDS, the SMEs can access more credit funds.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".